tensorflow.bazelrc

# TensorFlow Bazel configuration file.
# This file tries to group and simplify build options for TensorFlow
#
# ----CONFIG OPTIONS----
# Macosx options
#     darwin_arm64:
#
# Compiler options:
#     cuda_clang:             Use Clang when building CUDA code.
#     avx_linux:              Build with avx instruction set on linux.
#     avx_win:                Build with avx instruction set on windows
#
# Other build options:
#     short_logs:       Only log errors during build, skip warnings.
#     verbose_logs:     Show all compiler warnings during build.
#     monolithic:       Build all TF C++ code into a single shared object.
#     dynamic_kernels:  Try to link all kernels dynamically (experimental).
#     dbg:              Build with debug info
#
# TF version options;
#     v2: Build TF v2
#
# Feature and Third party library support options:
#     xla:          Build TF with XLA
#     tpu:          Build TF with TPU support
#     cuda:         Build with CUDA support.
#     cuda_clang    Build with CUDA Clang support.
#     rocm:         Build with AMD GPU support (rocm)
#     mkl:          Enable full mkl support.
#     nonccl:       Disable nccl support.
#
# PJRT Releases:
#     pjrt_{x86,aarch64}: Used to build PJRT CPU plugins.
#     pjrt_{x86,aarch64}_{cuda12,cuda13}: Used to build PJRT GPU plugins.
#
#
# Remote build execution options (only configured to work with TF team projects for now.)
#     rbe_base:                       General RBE options shared by all flavors.
#     rbe_linux:                      General RBE options used on all linux builds.
#     rbe_win_base:                   General RBE options used on all Windows builds. Not to be used standalone.
#     rbe_windows_x86_cpu_2022:       Windows-specific RBE options.
#
#     rbe_linux_cpu:                  RBE options to build with only CPU support.
#     rbe_linux_cuda:                 RBE options to build with GPU support using clang.
#     rbe_linux_cuda_nvcc:            RBE options to build with GPU support using nvcc.
#
# Embedded Linux options (experimental and only tested with TFLite build yet)
#     elinux:          General Embedded Linux options shared by all flavors.
#     elinux_aarch64:  Embedded Linux options for aarch64 (ARM64) CPU support.
#     elinux_armhf:    Embedded Linux options for armhf (ARMv7) CPU support.
#
# Default build options. These are applied first and unconditionally.

# For projects which use TensorFlow as part of a Bazel build process, putting
# nothing in a bazelrc will default to a monolithic build. The following line
# opts in to modular op registration support by default.
common --define framework_shared_object=true
common --define tsl_protobuf_header_only=true

common --define=allow_oversize_protos=true

common --spawn_strategy=standalone
common -c opt

common --repo_env=USE_PYWRAP_RULES=True
common --copt=-DGRPC_BAZEL_BUILD
common --host_copt=-DGRPC_BAZEL_BUILD
common --action_env=GRPC_BAZEL_RUNTIME=1
common --repo_env=PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=upb
common --action_env=PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=upb
# Some targets have the same py source file, but use different
# configurations via `requires-` tags. This results in an action
# conflict when precompiling. Disable to avoid that problem.
# See https://github.com/bazel-contrib/rules_python/issues/2445
common --@rules_python//python/config_settings:precompile=force_disabled
common --@rules_python//python/config_settings:bootstrap_impl=script --repo_env=RULES_PYTHON_ENABLE_PIPSTAR=0

# Do not do this. This is how gRPC builds itself by default, but we don't want
# that as it would link protobuf into its own set of dynamic libraries, which
# would conflict with our protobuf linkage.
#common --define=use_fast_cpp_protos=true

common --incompatible_default_to_explicit_init_py

# For local build, without dependency on rbe
common:linux_cpu --config=avx_linux
common:linux_cpu --linkopt=-lrt
common:linux_cpu --host_linkopt=-lrt
common:linux_cpu --linkopt=-lm
common:linux_cpu --host_linkopt=-lm
common:linux_cpu --config=avx_linux
common:linux_cpu --copt=-Wno-error=unused-command-line-argument
common:linux_cpu --copt=-Wno-gnu-offsetof-extensions

# Make Bazel print out all options from rc files.
common --announce_rc

# TODO(mihaimaruseac): Document this option or remove if no longer needed
common --define=grpc_no_ares=true

# See https://github.com/bazelbuild/bazel/issues/7362 for information on what
# --incompatible_remove_legacy_whole_archive flag does.
# This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate
# Tensorflow to the default, however test coverage wasn't enough to catch the
# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and
# then tackle this issue again.
#
# TODO: Remove the following two lines once TF doesn't depend on Bazel wrapping
# all library archives in -whole_archive -no_whole_archive.
common --noincompatible_remove_legacy_whole_archive
common --features=-force_no_whole_archive

# TODO(mihaimaruseac): Document this option or remove if no longer needed
common --enable_platform_specific_config

# TODO(mihaimaruseac): Document this option or remove if no longer needed
common --config=short_logs

# Precompiling results in some action conflicts. Disable it for now until
# the problematic targets are fixed.
common --@rules_python//python/config_settings:precompile=force_disabled

# TF now has `cc_shared_library` targets, so it needs the experimental flag
# TODO(rostam): Remove when `cc_shared_library` is enabled by default
common --experimental_cc_shared_library

# cc_shared_library ensures no library is linked statically more than once.
common --experimental_link_static_libraries_once=false

# Prevent regressions on those two incompatible changes
# TODO: remove those flags when they are flipped in the default Bazel version TF uses.
common --incompatible_enforce_config_setting_visibility
# TODO: also enable this flag after fixing the visibility violations
# common --incompatible_config_setting_private_default_visibility

# Print a stacktrace when a test is killed
test --test_env="GTEST_INSTALL_FAILURE_SIGNAL_HANDLER=1"


# Default options should come above this line.

# Sets the default Apple platform to macOS.
common:macos --apple_platform_type=macos

# Use cc toolchains from apple_support for Apple builds.
# https://github.com/bazelbuild/apple_support/tree/master?tab=readme-ov-file#bazel-6-setup
common:macos --apple_crosstool_top=@local_config_apple_cc//:toolchain
common:macos --crosstool_top=@local_config_apple_cc//:toolchain
common:macos --host_crosstool_top=@local_config_apple_cc//:toolchain

# gRPC on MacOS requires this #define
common:macos --copt=-DGRPC_BAZEL_BUILD

# Avoid hitting command line argument limit
common:macos --features=archive_param_file

# Settings for MacOS on ARM CPUs.
common:macos_arm64 --cpu=darwin_arm64
common:macos_arm64 --macos_minimum_os=11.0
common:macos_arm64 --platforms=@build_bazel_apple_support//platforms:darwin_arm64

# Config to use a mostly-static build and disable modular op registration
# support (this will revert to loading TensorFlow with RTLD_GLOBAL in Python).
# By default, TensorFlow will build with a dependence on
# //tensorflow:libtensorflow_framework.so.
common:monolithic --define framework_shared_object=false
common:monolithic --define tsl_protobuf_header_only=false
common:monolithic --experimental_link_static_libraries_once=false  # b/229868128

# Please note that MKL on MacOS is still not supported.
# If you would like to use a local MKL instead of downloading, please set the
# environment variable "TF_MKL_ROOT" every time before build.
common:mkl --define=build_with_mkl=true --define=enable_mkl=true
common:mkl --define=tensorflow_mkldnn_contraction_kernel=0
common:mkl --define=build_with_openmp=true
common:mkl -c opt

# config to build OneDNN backend with a user specified threadpool.
common:mkl_threadpool --define=build_with_mkl=true --define=enable_mkl=true
common:mkl_threadpool --define=tensorflow_mkldnn_contraction_kernel=0
common:mkl_threadpool --define=build_with_mkl_opensource=true
common:mkl_threadpool -c opt

# Config setting to build oneDNN with Compute Library for the Arm Architecture (ACL).
# with Eigen threadpool support
common:mkl_aarch64_threadpool --define=build_with_mkl_aarch64=true
common:mkl_aarch64_threadpool -c opt

# This is an alias for the mkl_aarch64_threadpool build.
common:mkl_aarch64 --config=mkl_aarch64_threadpool

# Default CUDA, CUDNN, NCCL and NVSHMEM versions.
common:cuda_version --repo_env=HERMETIC_CUDA_VERSION="12.9.1"
common:cuda_version --repo_env=HERMETIC_CUDNN_VERSION="9.8.0"
common:cuda_version --repo_env=HERMETIC_NVSHMEM_VERSION="3.2.5"
common:cuda_version --repo_env=HERMETIC_NCCL_VERSION="2.28.9"

# CUDA: This config refers to building CUDA op kernels with nvcc.
common:cuda --repo_env TF_NEED_CUDA=1
common:cuda --@rules_ml_toolchain//common:enable_cuda
common:cuda --config=cuda_version
# This flag is needed to include CUDA libraries.
common:cuda --@local_config_cuda//cuda:include_cuda_libs=true

# This configuration is used for building the wheels.
common:cuda_wheel --@local_config_cuda//cuda:include_cuda_libs=false

common:hermetic_cuda_umd --@cuda_driver//:include_cuda_umd_libs=true

# CUDA: This config refers to building CUDA op kernels with clang.
common:cuda_clang --config=cuda
common:cuda_clang --@local_config_cuda//:cuda_compiler=clang
common:cuda_clang --copt=-Qunused-arguments
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current
# major release. Example: sm_80 kernels can run on sm_89 GPUs but
# not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs.
common:cuda_clang --repo_env=HERMETIC_CUDA_COMPUTE_CAPABILITIES="sm_60,sm_70,sm_80,sm_89,compute_90"
# Permit newer CUDA versions than Clang is aware of
common:cuda_clang --copt="-Wno-unknown-cuda-version"
# Set lld as the linker.
common:cuda_clang --host_linkopt="-fuse-ld=lld"
common:cuda_clang --host_linkopt="-lm"
common:cuda_clang --linkopt="-fuse-ld=lld"
common:cuda_clang --linkopt="-lm"

common:cuda_clang_local --config=cuda_clang
common:cuda_clang_local --config=clang_local
common:cuda_clang_local --crosstool_top=@local_config_cuda//crosstool:toolchain

# Set up compilation CUDA version and paths and use the CUDA Clang toolchain.
common:cuda_clang_official --config=cuda_clang
common:cuda_clang_official --config=cuda_version
common:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-18/bin/clang"
common:cuda_clang_official --crosstool_top="@local_config_cuda//crosstool:toolchain"

# Build with nvcc for CUDA and clang for host
common:cuda_nvcc --config=cuda
common:cuda_nvcc --action_env=TF_NVCC_CLANG="1"
common:cuda_nvcc --@local_config_cuda//:cuda_compiler=nvcc
# Old config for backward compatibility
common:nvcc_clang --config=cuda_nvcc

# Deprecated cuda_nvcc config with non-hermetic toolchains
common:cuda_nvcc_clang_local --config=cuda_nvcc
common:cuda_nvcc_clang_local --config=clang_local
common:cuda_nvcc_clang_local --crosstool_top=@local_config_cuda//crosstool:toolchain

# Debug config. Enables Bazel's 'dbg' compilation mode, build with debugging enabled
common:dbg -c dbg
# Compiling all dependencies with debug info can cause linker failures
# and significantly increase binary size.
# The following setting disables debug info (-g0) for all files,
# except those under the xla/* path. This helps reduce the size of debug sections
# in the ELF binary, which can otherwise become too large and lead to errors.
# For more details, see: https://github.com/tensorflow/tensorflow/issues/48919.
common:dbg --per_file_copt=+.*,-xla.*@-g0
# AWS SDK must be compiled in release mode. see: https://github.com/tensorflow/tensorflow/issues/37498
common:dbg --copt -DDEBUG_BUILD

common:asan --strip=never
common:asan --copt -fsanitize=address
common:asan --copt -DADDRESS_SANITIZER
common:asan --copt -O1
common:asan --copt -g
common:asan --copt -fno-omit-frame-pointer
common:asan --linkopt -fsanitize=address

common:rocm_base --config=clang_local
common:rocm_base --copt=-Wno-gnu-offsetof-extensions
common:rocm_base --crosstool_top=@local_config_rocm//crosstool:toolchain
common:rocm_base --define=using_rocm_hipcc=true
common:rocm_base --define=tensorflow_mkldnn_contraction_kernel=0
common:rocm_base --repo_env TF_NEED_ROCM=1

common:rocm_clang_official --config=rocm_base
common:rocm_clang_official --action_env=CLANG_COMPILER_PATH="/usr/lib/llvm-18/bin/clang"
common:rocm_clang_official --action_env=HIPCC_COMPILE_FLAGS_APPEND="--offload-compress"
common:rocm_clang_official --action_env=TF_ROCM_CLANG="1"
common:rocm_clang_official --linkopt="-fuse-ld=lld"
common:rocm_clang_official --host_linkopt="-fuse-ld=lld"

common:rocm --config=rocm_clang_official
common:rocm_ci --config=rocm

common:rocm_ci_hermetic --dynamic_mode=off
common:rocm_ci_hermetic --config=rocm_clang_official
common:rocm_ci_hermetic --repo_env="ROCM_DISTRO_VERSION=rocm_7.10.0_gfx90X"
common:rocm_ci_hermetic --@local_config_rocm//rocm:rocm_path_type=hermetic

# This config option is used for SYCL as GPU backend.
# SYCL Configuration (non-hermetic)
common:sycl --@rules_ml_toolchain//common:enable_sycl=True
common:sycl --repo_env=TF_NEED_SYCL=1
common:sycl --define=tensorflow_mkldnn_contraction_kernel=0
common:sycl --cxxopt=-std=c++17
common:sycl --host_cxxopt=-std=c++17
common:sycl --repo_env=SYCL_BUILD_HERMETIC=0

# Enable Clang for host and icpx for SYCL
common:icpx_clang --repo_env TF_ICPX_CLANG=1
common:icpx_clang --copt=-fclang-abi-compat=17

# Hermetic SYCL Configuration
common:sycl_hermetic --config=sycl
common:sycl_hermetic --repo_env=SYCL_BUILD_HERMETIC=1

# Options to disable default on features
common:nonccl --define=no_nccl_support=true

# Don't trigger --config=<host platform> when cross-compiling.
common:linux --host_copt=-w
common:macos --copt=-w
common:windows --copt=/W0
common:windows --host_copt=/W0

# Linux ARM64 specific options
common:linux_arm64 --copt="-mtune=generic" --copt="-march=armv8-a" --copt="-O3"


# On Windows, `__cplusplus` is wrongly defined without this switch
# See https://devblogs.microsoft.com/cppblog/msvc-now-correctly-reports-__cplusplus/
common:windows --copt=/Zc:__cplusplus
common:windows --host_copt=/Zc:__cplusplus

# Tensorflow uses M_* math constants that only get defined by MSVC headers if
# _USE_MATH_DEFINES is defined.
common:windows --copt=/D_USE_MATH_DEFINES
common:windows --host_copt=/D_USE_MATH_DEFINES

# Windows has a relatively short command line limit, which TF has begun to hit.
# See https://docs.bazel.build/versions/main/windows.html
common:windows --features=compiler_param_file
common:windows --features=archive_param_file

# Speed Windows compile times. Available in VS 16.4 (we are on 16.11). See
# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion
common:windows --copt=/d2ReducedOptimizeHugeFunctions
common:windows --host_copt=/d2ReducedOptimizeHugeFunctions

# Before VS 2017 15.8, the member "type" would non-conformingly have an
# alignment of only alignof(max_align_t). VS 2017 15.8 was fixed to handle this
# correctly, but the fix inherently changes layout and breaks binary
# compatibility (*only* for uses of aligned_storage with extended alignments).
common:windows --copt=-D_ENABLE_EXTENDED_ALIGNED_STORAGE
common:windows --host_copt=-D_ENABLE_EXTENDED_ALIGNED_STORAGE

# Enable the runfiles symlink tree on Windows. This makes it possible to build
# the pip package on Windows without an intermediate data-file archive, as the
# build_pip_package script in its current form (as of Aug 2023) uses the
# runfiles symlink tree to decide what to put into the Python wheel.
startup --windows_enable_symlinks
common:windows --enable_runfiles
common:windows --nobuild_python_zip
common:windows --dynamic_mode=off

# Default paths for TF_SYSTEM_LIBS
common:linux --define=PREFIX=/usr
common:linux --define=LIBDIR=$(PREFIX)/lib
common:linux --define=INCLUDEDIR=$(PREFIX)/include
common:linux --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include
common:macos --define=PREFIX=/usr
common:macos --define=LIBDIR=$(PREFIX)/lib
common:macos --define=INCLUDEDIR=$(PREFIX)/include
common:macos --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include
# TF_SYSTEM_LIBS do not work on windows.

# By default, build TF in C++ 17 mode.
common:linux --cxxopt=-std=c++17
common:linux --host_cxxopt=-std=c++17
common:macos --cxxopt=-std=c++17
common:macos --host_cxxopt=-std=c++17
common:windows --cxxopt=/std:c++17
common:windows --host_cxxopt=/std:c++17

# On windows, we still link everything into a single DLL.
common:windows --config=monolithic

# Make sure to include as little of windows.h as possible
common:windows --copt=-DWIN32_LEAN_AND_MEAN
common:windows --host_copt=-DWIN32_LEAN_AND_MEAN
common:windows --copt=-DNOGDI
common:windows --host_copt=-DNOGDI

# MSVC (Windows): Standards-conformant preprocessor mode
# See https://docs.microsoft.com/en-us/cpp/preprocessor/preprocessor-experimental-overview
common:windows --copt=/Zc:preprocessor
common:windows --host_copt=/Zc:preprocessor

# Misc build options we need for windows.
common:windows --linkopt=/DEBUG
common:windows --host_linkopt=/DEBUG
common:windows --linkopt=/OPT:REF
common:windows --host_linkopt=/OPT:REF
common:windows --linkopt=/OPT:ICF
common:windows --host_linkopt=/OPT:ICF

# Verbose failure logs when something goes wrong
common:windows --verbose_failures

# Work around potential issues with large command lines on windows.
# See: https://github.com/bazelbuild/bazel/issues/5163
common:windows --features=compiler_param_file

# Do not risk cache corruption. See:
# https://github.com/bazelbuild/bazel/issues/3360
common:linux --experimental_guard_against_concurrent_changes

# Configure short or long logs
common:short_logs --output_filter=DONT_MATCH_ANYTHING
common:verbose_logs --output_filter=

# Instruction set optimizations
# TODO(gunan): Create a feature in toolchains for avx/avx2 to
#   avoid having to define linux/win separately.
common:avx_linux --copt=-mavx
common:avx_linux --host_copt=-mavx
common:avx_win --copt=/arch:AVX

common:win_clang_base --@com_google_protobuf//build_defs:use_dlls=True
common:win_clang_base --@com_google_absl//absl:use_dlls=True
common:win_clang_base --linkopt=/demangle:no --host_linkopt=/demangle:no
common:win_clang_base --linkopt=/errorlimit:0 --host_linkopt=/errorlimit:0
common:win_clang_base --copt=/clang:-Weverything
common:win_clang_base --host_copt=/clang:-Weverything
common:win_clang_base --compiler=clang-cl
common:win_clang_base --linkopt=/FORCE:MULTIPLE
common:win_clang_base --host_linkopt=/FORCE:MULTIPLE
common:win_clang_base --action_env=PATHEXT=.COM;.EXE;.BAT;.CMD;.VBS;.VBE;.JS;.JSE;.WSF;.WSH;.MSC;.PY;.PYW
test:win_clang_base --linkopt=/FORCE:MULTIPLE
test:win_clang_base --host_linkopt=/FORCE:MULTIPLE
test:win_clang_base --build_tests_only --keep_going --test_output=errors --verbose_failures=true --test_summary=short

common:win_clang --config=win_clang_base
common:win_clang --extra_toolchains=@local_config_cc//:cc-toolchain-x64_windows-clang-cl
common:win_clang --extra_execution_platforms=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
common:win_clang --host_platform=//tensorflow/tools/toolchains/win:x64_windows-clang-cl

common:windows_x86_cpu_2022 --config=win_clang_base
common:windows_x86_cpu_2022 --crosstool_top="//tensorflow/tools/toolchains/win2022/20241118:toolchain"
common:windows_x86_cpu_2022 --extra_toolchains="//tensorflow/tools/toolchains/win2022/20241118:cc-toolchain-x64_windows-clang-cl"
common:windows_x86_cpu_2022 --extra_execution_platforms="//tensorflow/tools/toolchains/win2022:windows_ltsc2022_clang"
common:windows_x86_cpu_2022 --host_platform="//tensorflow/tools/toolchains/win2022:windows_ltsc2022_clang"
common:windows_x86_cpu_2022 --platforms="//tensorflow/tools/toolchains/win2022:windows_ltsc2022_clang"

common:xla_windows_x86_cpu_2022 --config=win_clang_base
common:xla_windows_x86_cpu_2022 --crosstool_top="//tools/toolchains/win2022/20241118:toolchain"
common:xla_windows_x86_cpu_2022 --extra_toolchains="//tools/toolchains/win2022/20241118:cc-toolchain-x64_windows-clang-cl"
common:xla_windows_x86_cpu_2022 --extra_execution_platforms="//tools/toolchains/win2022:windows_ltsc2022_clang"
common:xla_windows_x86_cpu_2022 --host_platform="//tools/toolchains/win2022:windows_ltsc2022_clang"
common:xla_windows_x86_cpu_2022 --platforms="//tools/toolchains/win2022:windows_ltsc2022_clang"

# Options to build TensorFlow 1.x or 2.x.
# TODO(kanglan): Change v2's define to default behavior
common:v2 --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

# Enable all targets in XLA
common:cpu_cross --define=with_cross_compiler_support=true

# BEGIN TF REMOTE BUILD EXECUTION OPTIONS
# Options when using remote execution
# WARNING: THESE OPTIONS WONT WORK IF YOU DO NOT HAVE PROPER AUTHENTICATION AND PERMISSIONS

# Allow creation of resultstore URLs for any bazel invocation
common:resultstore --google_default_credentials
common:resultstore --bes_backend=buildeventservice.googleapis.com
common:resultstore --bes_instance_name="tensorflow-testing"
common:resultstore --bes_results_url="https://source.cloud.google.com/results/invocations"
common:resultstore --bes_timeout=600s

# Flag to enable remote config
common --experimental_repo_remote_exec

common:use_tar_archive_files --repo_env=USE_CUDA_TAR_ARCHIVE_FILES=1
common:use_tar_archive_files --repo_env=USE_NVSHMEM_TAR_ARCHIVE_FILES=1
common:use_tar_archive_files --repo_env=USE_LLVM_TAR_ARCHIVE_FILES=1
common:use_tar_archive_files --repo_env=USE_MIRRORED_TAR_ARCHIVE_FILES=1

# Make Bazel not try to probe the host system for a C++ toolchain.
common:rbe_base --config=resultstore
common:rbe_base --define=EXECUTOR=remote
common:rbe_base --jobs=800
common:rbe_base --remote_executor=grpcs://remotebuildexecution.googleapis.com
common:rbe_base --remote_timeout=3600
common:rbe_base --spawn_strategy=remote,worker,standalone,local
# Attempt to minimize the amount of data transfer between bazel and the remote
# workers:
common:rbe_base --remote_download_toplevel
test:rbe_base --test_env=USER=anon

# TODO(kanglan): Check if we want to merge rbe_linux into rbe_linux_cpu.
common:rbe_linux --config=rbe_base
common:rbe_linux --action_env=PATH="/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin"
# Non-rbe settings we should include because we do not run configure
common:rbe_linux --config=avx_linux
# TODO(gunan): Check why we need this specified in rbe, but not in other builds.
common:rbe_linux --linkopt=-lrt
common:rbe_linux --host_linkopt=-lrt
common:rbe_linux --linkopt=-lm
common:rbe_linux --host_linkopt=-lm

common:rbe_linux_cpu --config=rbe_linux
# Linux cpu and cuda builds share the same toolchain now.
common:rbe_linux_cpu --extra_execution_platforms="@ml_build_config_platform//:platform"
common:rbe_linux_cpu --host_platform="@ml_build_config_platform//:platform"
common:rbe_linux_cpu --platforms="@ml_build_config_platform//:platform"
# This is needed for all Clang17 builds but must not be present in GCC builds.
common:rbe_linux_cpu --copt=-Wno-error=unused-command-line-argument
# This was added in clang-16 by https://reviews.llvm.org/D133574.
# Can be removed once upb is updated, since a type definition is used within
# offset of in the current version of ubp.
# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.
common:rbe_linux_cpu --copt=-Wno-gnu-offsetof-extensions
# Python config is the same across all containers because the binary is the same
common:rbe_linux_cpu --python_path="/usr/bin/python3"
# These you may need to change for your own GCP project.
common:rbe_linux_cpu --remote_instance_name=projects/tensorflow-testing/instances/default_instance

# Deprecated RBE config with non-hermetic toolchains.
common:rbe_linux_cpu_clang_local --config=clang_local
common:rbe_linux_cpu_clang_local --config=rbe_linux_cpu
common:rbe_linux_cpu_clang_local --repo_env=BAZEL_DO_NOT_DETECT_CPP_TOOLCHAIN=1
common:rbe_linux_cpu_clang_local --host_crosstool_top="@local_config_cuda//crosstool:toolchain"
common:rbe_linux_cpu_clang_local --crosstool_top="@local_config_cuda//crosstool:toolchain"
common:rbe_linux_cpu_clang_local --extra_toolchains="@local_config_cuda//crosstool:toolchain-linux-x86_64"
common:rbe_linux_cpu_clang_local --repo_env=CC="/usr/lib/llvm-18/bin/clang"
common:rbe_linux_cpu_clang_local --repo_env=TF_SYSROOT="/dt9"

common:rbe_linux_cuda --config=cuda_clang_official
common:rbe_linux_cuda --config=rbe_linux_cpu
# dt9 is based on glibc 2.17, which is outdated and incompatible with CUDA 12.8.0
# unset TF_SYSROOT
common:rbe_linux_cuda --repo_env=TF_SYSROOT=
# For Remote build execution -- GPU configuration
common:rbe_linux_cuda --repo_env=REMOTE_GPU_TESTING=1
# Update UMD version when RBE CUDA driver is updated.
common:rbe_linux_cuda --repo_env=HERMETIC_CUDA_UMD_VERSION="13.0.2"

common:rbe_linux_cuda_nvcc --config=rbe_linux_cuda
common:rbe_linux_cuda_nvcc --config=cuda_nvcc
common:rbe_linux_cuda_nvcc --repo_env TF_NCCL_USE_STUB=1

common:rbe_win_base --config=clang_local
common:rbe_win_base --config=rbe_base
common:rbe_win_base --repo_env=BAZEL_DO_NOT_DETECT_CPP_TOOLCHAIN=1
common:rbe_win_base --shell_executable=C:\\tools\\msys64\\usr\\bin\\bash.exe
common:rbe_win_base --remote_instance_name=projects/tensorflow-testing/instances/windows
# Don't build the python zip archive in the RBE build.
common:rbe_win_base --remote_download_minimal
common:rbe_win_base --enable_runfiles
common:rbe_win_base --nobuild_python_zip
# Don't build the runfile links in the RBE build which is expensive on Windows.
common:rbe_win_base --nobuild_runfile_links
common:rbe_win_base --define=override_eigen_strong_inline=true

common:rbe_windows_x86_cpu_2022 --config=rbe_win_base --config=windows_x86_cpu_2022

# Override the remote instance and BES instance names to use the new RBE pools
common:rbe_windows_x86_cpu_2022 --remote_instance_name=projects/ml-oss-rbe-general/instances/default_instance
common:rbe_windows_x86_cpu_2022 --bes_instance_name="ml-oss-rbe-general"

common:rbe_windows_x86_cpu_2022 --host_platform="//tensorflow/tools/toolchains/win2022:windows_ltsc2022_clang_new"
common:rbe_windows_x86_cpu_2022 --extra_execution_platforms="//tensorflow/tools/toolchains/win2022:windows_ltsc2022_clang_new"
common:rbe_windows_x86_cpu_2022 --platforms="//tensorflow/tools/toolchains/win2022:windows_ltsc2022_clang_new"

common:rbe_xla_windows_x86_cpu_2022 --config=rbe_win_base --config=xla_windows_x86_cpu_2022
common:rbe_xla_windows_x86_cpu_2022 --remote_instance_name=projects/ml-oss-rbe-general/instances/default_instance
common:rbe_xla_windows_x86_cpu_2022 --bes_instance_name="ml-oss-rbe-general"

common:rbe_xla_windows_x86_cpu_2022 --host_platform="//tools/toolchains/win2022:windows_ltsc2022_clang_new"
common:rbe_xla_windows_x86_cpu_2022 --extra_execution_platforms="//tools/toolchains/win2022:windows_ltsc2022_clang_new"
common:rbe_xla_windows_x86_cpu_2022 --platforms="//tools/toolchains/win2022:windows_ltsc2022_clang_new"

# END TF REMOTE BUILD EXECUTION OPTIONS

# TFLite build configs for generic embedded Linux
common:elinux --config=clang_local
common:elinux --crosstool_top=@local_config_embedded_arm//:toolchain
common:elinux --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
common:elinux_aarch64 --config=elinux
common:elinux_aarch64 --cpu=aarch64
common:elinux_aarch64 --platforms=@org_tensorflow//tensorflow/tools/toolchains/linux:linux_aarch64
common:elinux_armhf --config=elinux
common:elinux_armhf --cpu=armhf
common:elinux_armhf --platforms=@org_tensorflow//tensorflow/tools/toolchains/linux:linux_armhf
common:elinux_armhf --copt -mfp16-format=ieee

# Config-specific options should come above this line.

# Load rc file written by ./configure.
try-import %workspace%/.tf_configure.bazelrc

# Load rc file with user-specific options.
try-import %workspace%/.bazelrc.user

common:release_cpu_macos --config=avx_linux

# Base build configs for macOS
common:release_macos_base --define=no_nccl_support=true --output_filter=^$

# Ensure release_base is set on mac
common:release_macos_base --config=cpu_cross
common:release_macos_base --config=clang_local

# Build configs for macOS x86
common:release_macos_x86 --config=release_macos_base
# Build with the AVX instruction set when on macOS x86
common:release_macos_x86 --config=avx_linux
common:release_macos_x86 --cpu=darwin
common:release_macos_x86 --platforms=@build_bazel_apple_support//platforms:darwin_x86_64
# Target Catalina as the minimum compatible OS version
common:release_macos_x86 --macos_minimum_os=10.15
common:release_macos_x86 --macos_sdk_version=10.15

# Build configs for macOS Arm64
common:release_macos_arm64 --config=release_macos_base
common:release_macos_arm64 --cpu=darwin_arm64
common:release_macos_arm64 --platforms=@build_bazel_apple_support//platforms:darwin_arm64
common:release_macos_arm64 --define=tensorflow_mkldnn_contraction_kernel=0
# Target Moneterey as the minimum compatible OS version
common:release_macos_arm64 --macos_minimum_os=12.0
common:release_macos_arm64 --macos_sdk_version=12.0

# Base test configs for macOS
test:release_macos_base --verbose_failures=true --local_test_jobs=HOST_CPUS
test:release_macos_base --test_timeout=300,450,1200,3600 --test_output=errors
test:release_macos_base --build_tests_only --keep_going
test:release_macos_base --flaky_test_attempts=3

# Test configs for macOS x86
test:release_macos_x86 --config=release_macos_base

# BEGIN TF CACHE HELPER OPTIONS
# Options when using remote execution
# WARNING: THESE OPTIONS WONT WORK IF YOU DO NOT HAVE PROPER AUTHENTICATION AND PERMISSIONS

# Use --config=tf_public_cache to try and use the TensorFlow public build cache
# to build TensorFlow. Look at ci/official/envs to find which types of jobs
# push to the cache.  For macOS, use --config=tf_public_macos_cache
common:tf_public_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/january2024" --remote_upload_local_results=false
# Cache pushes are limited to TF's CI system.
common:tf_public_cache_push --config=tf_public_cache --remote_upload_local_results=true --google_default_credentials
# Public cache for macOS builds
common:tf_public_macos_cache --remote_cache="https://storage.googleapis.com/tensorflow-macos-bazel-cache/oct2023" --remote_upload_local_results=false
# Cache pushes are limited to TF's CI system.
common:tf_public_macos_cache_push --config=tf_public_macos_cache --remote_upload_local_results=true --google_default_credentials

# END TF CACHE HELPER OPTIONS

# START CROSS-COMPILE CONFIGS
# Set execution platform to Linux x86
# Note: Lot of the "host_" flags such as "host_cpu" and "host_crosstool_top"
# flags seem to be actually used to specify the execution platform details. It
# seems it is this way because these flags are old and predate the distinction
# between host and execution platform.
common:cross_compile_base --config=clang_local
common:cross_compile_base --host_cpu=k8
common:cross_compile_base --host_crosstool_top=//tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
common:cross_compile_base --extra_execution_platforms=//tools/toolchains/cross_compile/config:linux_x86_64

common:rbe_cross_compile_base --config=rbe_base
common:rbe_cross_compile_base --repo_env=BAZEL_DO_NOT_DETECT_CPP_TOOLCHAIN=1
common:rbe_cross_compile_base --remote_instance_name=projects/tensorflow-testing/instances/default_instance

# Test-related settings below this point
# We cannot run cross-compiled tests on the remote Linux x86 VMs so we need to
# force all tests to run locally on the Aarch64 host.
test:rbe_cross_compile_base --strategy=TestRunner=local --build_tests_only
test:rbe_cross_compile_base --verbose_failures=true --local_test_jobs=HOST_CPUS --test_output=errors

# START LINUX AARCH64 CROSS-COMPILE CONFIGS
common:cross_compile_linux_arm64 --config=cross_compile_base

# Set the target CPU to Aarch64
common:cross_compile_linux_arm64 --platforms=//tools/toolchains/cross_compile/config:linux_aarch64
common:cross_compile_linux_arm64 --cpu=aarch64
common:cross_compile_linux_arm64 --crosstool_top=//tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite

# RBE cross-compile configs for Linux Aarch64
common:rbe_cross_compile_linux_arm64 --config=cross_compile_linux_arm64
common:rbe_cross_compile_linux_arm64 --config=rbe_cross_compile_base
test:rbe_cross_compile_linux_arm64 --config=rbe_cross_compile_base

# END LINUX AARCH64 CROSS-COMPILE CONFIGS

# START MACOS CROSS-COMPILE CONFIGS
common:cross_compile_macos_x86 --config=cross_compile_base
common:cross_compile_macos_x86 --config=nonccl
# Target Catalina (10.15) as the minimum supported OS
common:cross_compile_macos_x86 --action_env  MACOSX_DEPLOYMENT_TARGET=10.15

# Set the target CPU to Darwin x86
common:cross_compile_macos_x86 --platforms=//tools/toolchains/cross_compile/config:darwin_x86_64
common:cross_compile_macos_x86 --cpu=darwin
common:cross_compile_macos_x86 --crosstool_top=//tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
# When RBE cross-compiling for macOS, we need to explicitly register the
# toolchain. Otherwise, oddly, RBE complains that a "docker container must be
# specified".
common:cross_compile_macos_x86 --extra_toolchains=//tools/toolchains/cross_compile/config:macos-x86-cross-compile-cc-toolchain
# Map --platforms=darwin_x86_64 to --cpu=darwin and vice-versa to make selects()
# and transistions that use these flags work.
common:cross_compile_macos_x86 --platform_mappings=tools/toolchains/cross_compile/config/platform_mappings

# RBE cross-compile configs for Darwin x86
common:rbe_cross_compile_macos_x86 --config=cross_compile_macos_x86 --remote_download_minimal
common:rbe_cross_compile_macos_x86 --bes_backend="" --bes_results_url="" --bes_timeout="0s"
common:rbe_cross_compile_macos_x86 --experimental_remote_build_event_upload="minimal"
common:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base
common:rbe_cross_compile_macos_x86 --bes_upload_mode=nowait_for_upload_complete
test:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base
# Increase the test timeout as tests often take longer on mac.
test:rbe_cross_compile_macos_x86 --test_timeout=300,450,1200,3600
# Limit jobs to 100 to avoid running into "out of memory" issues (b/316266643)
common:rbe_cross_compile_macos_x86 --jobs=100
test:rbe_cross_compile_macos_x86 --jobs=100
# END MACOS CROSS-COMPILE CONFIGS
# END CROSS-COMPILE CONFIGS

# START PJRT RELEASE CONFIGS
build:pjrt_release -c opt --@local_config_cuda//cuda:include_cuda_libs=false
build:pjrt_nightly -c opt --@local_config_cuda//cuda:include_cuda_libs=true

build:pjrt_x86 --cpu=k8
build:pjrt_aarch64 --cpu=aarch64

build:pjrt_cuda12 --config=cuda_nvcc
build:pjrt_cuda12 --repo_env=HERMETIC_CUDA_VERSION="12.9.1"
build:pjrt_cuda12 --repo_env=HERMETIC_CUDNN_VERSION="9.8.0"
build:pjrt_cuda12 --repo_env=HERMETIC_NVSHMEM_VERSION="3.2.5"
build:pjrt_cuda12 --repo_env=HERMETIC_CUDA_COMPUTE_CAPABILITIES="sm_50,sm_60,sm_70,sm_80,sm_90,sm_100,compute_120"

build:pjrt_cuda13 --config=cuda_nvcc
build:pjrt_cuda13 --repo_env=HERMETIC_CUDA_VERSION="13.0.0"
build:pjrt_cuda13 --repo_env=HERMETIC_CUDNN_VERSION="9.12.0"
build:pjrt_cuda13 --repo_env=HERMETIC_NVSHMEM_VERSION="3.3.20"
build:pjrt_cuda13 --repo_env=HERMETIC_CUDA_COMPUTE_CAPABILITIES="sm_75,sm_80,sm_90,sm_100,compute_120"

build:pjrt_x86_release --config=pjrt_release --config=pjrt_x86
build:pjrt_aarch64_release --config=pjrt_release --config=pjrt_aarch64
build:pjrt_x86_nightly --config=pjrt_nightly --config=pjrt_x86
build:pjrt_aarch64_nightly --config=pjrt_nightly --config=pjrt_aarch64

build:pjrt_x86_cuda12_release --config=pjrt_x86_release --config=pjrt_cuda12
build:pjrt_aarch64_cuda12_release --config=pjrt_aarch64_release --config=pjrt_cuda12
build:pjrt_x86_cuda13_release --config=pjrt_x86_release --config=pjrt_cuda13
build:pjrt_aarch64_cuda13_release --config=pjrt_aarch64_release --config=pjrt_cuda13

build:pjrt_x86_cuda12_nightly --config=pjrt_x86_nightly --config=pjrt_cuda12
build:pjrt_aarch64_cuda12_nightly --config=pjrt_aarch64_nightly --config=pjrt_cuda12
build:pjrt_x86_cuda13_nightly --config=pjrt_x86_nightly --config=pjrt_cuda13
build:pjrt_aarch64_cuda13_nightly --config=pjrt_aarch64_nightly --config=pjrt_cuda13
# END PJRT RELEASE CONFIGS